BISC 111/113:Lab3assign2012.docx

Lab 3 assignment descriptive version

Lab 3: Assignment

NOTE: The Science Writing Guidelines in the BISC 111/113 WIKI describe the importance of effectively designing a figure that is easily evaluated by the reader and it is recommended that you refer to this resource for more detailed information about a results section. We highly recommend using peer reviewed published journal articles as models for figure design and writing content.

Preparing a figure comparing mean ± SD Transpiration Rates:

This week you collected water loss and leaf surface area data from four different species of plants and converted those data into measures of transpiration rate and resistance to transpiration. To summarize these results graphically, you will create one effective figure and its accompanying caption comparing the mean ± SD transpiration rates for all four species in the two conditions (HLHW and LLLW). Excel tip: Chart>Source data> add series to add the LLLW data set.

What experimental question does the transpiration figure address? Does your figure demonstrate the answer to this question clearly? For example, if you were interested in which plants transpire the most in HLHW, in what order should the plants appear on your graph to emphasize this to the reader? If the data are not arranged in that order, how can you adjust the figure? How would you organize the columns if you were interested in whether or not the plants from drier environments will show lower transpiration rates?

Once you have a graphical representation of the mean±SD transpiration rates for each plant, you need to determine whether or not the means are significantly different from each other using statistics (JMP).

t-test: t-tests are used to compare means for two groups. For example your assignment asks you to conduct t-tests comparing a) transpiration and b) resistance in the HLHW condition to the LLLW condition for the plant species you investigated in lab today. Refer to the Stats and Graphing Folder guide if you are not sure how to perform a t-test in JMP. Brieflly: highlight the transpiration data for your three replicate plants in the light and in the dark, then create a TABLE: Subset. On this new JMP sheet there are only the 6 data points. Analyze: Fit Y by X: fill in the X and Y variable and click OK. On the graph that appears use the red triangle to select: Means/ANOVA/Pooled T. Is there a significant difference in mean transpiration in the light and dark for that plant? You can tell there is a difference if the probability that there is no treatment effect is “P”≤ 0.05. 5% of the time these means indicate no treatment effect, indicating that the likelihood is high that there is a treatment effect).

Consider following similar steps to compare transpiration rates in the sunflower and the water hyacinth in HLHW, and sunflower and Rhoeo in HLHW. What question are you trying to answer with each of these t-tests?

ANOVA: Since we actually measured four different plants (not two), you need to perform a one-way ANOVA to compare all four plants in one condition (e.g., HLHW OR LLLW). To perform the first of the assigned one-way ANOVAs select only the HLHW transpiration data. Click Table: subset and then Analyze: fit Y by X. Is there a significant difference among the means being compared (P ≤ 0.05)? If so, find out which group(s) is/are significantly different by using the drop down red triangle to COMPARE: means: Tukey HSD. The test results will be added to the analysis. Notice how the letters identify which groups are significantly different from the others.

Perform the remaining one-way ANOVAs assigned so you can evaluate differences among all four species for all the variables tested. If you forget how to use JMP, use the directions provided in the Stats and Graphing folder in SAKAI. We will not be using all the ANOVAs for today's graded assignment on transpiration, but you will find them helpful as you analyze the plant data over the next few weeks.

Figure caption

Place a caption under each figure, single-spaced. The caption should include: Figure number: A TITLE for the figure. Then, a brief summary explaining how the data in that figure were collected and/or calculated. A reader should be able to understand what you did to gather your data by examining the figure and reading the caption. Do not analyze or interpret the data in the caption (your instructor may modify these criteria and provide a model for you to follow, so take notes in lab).

Narrative of Results section

Write a Results text summarizing how your data answer the biological question(s) addressed in your transpiration rate figure. A Results text summarizes the main point(s) of a figure or table and analyzes the data to show how the biological question can be supported or not supported by the data.

For novice science writers, it might be helpful for you to start each paragraph of the Results text with a declarative statement of one of the main findings. This is a "topic sentence" that summarizes the details that follow in the paragraph. Do not repeat your methodology here, you will analyze the data but not offer any explanation or application of results. (Explanation and application would come in a Discussion section that would follow Results; here, you're goal is to analyze "the facts".) Your goal is to draw the attention of the reader to trends and patterns in the data, without repeating in words the numbers that appear in tables or figures. Cite the table and/or figure that supports your analysis (in parenthesis) and include the statistical information (in parenthesis) wherever you say there is an effect of treatment or a significant difference. Stats are used to evaluate if there is a treatment effect or if the difference between the means is not sufficient to preclude their being due to chance alone; they do not tell you about the biology behind your experiment. Embed the stats in the Results text as described in the science writing guidelines in the WIKI Results text guide. Build your Results text around your experimental hypothesis or question (focus on the biology) and present the data so that your hypothesis can be evaluated.